Pre-train, Adapt and Detect: Multi-Task Adapter Tuning for Camouflaged Object Detection

Camouflaged object detection (COD), aiming to segment camouflaged objects which exhibit similar patterns with the background, is a challenging task. Most existing works are dedicated to establishing specialized modules to identify camouflaged objects with complete and fine details, while the boundary can not be well located for the lack of object-related semantics. In this paper, we propose a novel ``pre-train, adapt and detect" paradigm to detect camouflaged objects. By introducing a large pre-trained model, abundant knowledge learned from massive multi-modal data can be directly transferred to COD. A lightweight parallel adapter is inserted to adjust the features suitable for the downstream COD task. Extensive experiments on four challenging benchmark datasets demonstrate that our method outperforms existing state-of-the-art COD models by large margins. Moreover, we design a multi-task learning scheme for tuning the adapter to exploit the shareable knowledge across different semantic classes. Comprehensive experimental results showed that the generalization ability of our model can be substantially improved with multi-task adapter initialization on source tasks and multi-task adaptation on target tasks

Germanium-lead perovskite light-emitting diodes.

Reducing environmental impact is a key challenge for perovskite optoelectronics, as most high-performance devices are based on potentially toxic lead-halide perovskites. For photovoltaic solar cells, tin-lead (Sn-Pb) perovskite materials provide a promising solution for reducing toxicity. However, Sn-Pb perovskites typically exhibit low luminescence efficiencies, and are not ideal for light-emitting applications. Here we demonstrate highly luminescent germanium-lead (Ge-Pb) perovskite films with photoluminescence quantum efficiencies (PLQEs) of up to ~71%, showing a considerable relative improvement of ~34% over similarly prepared Ge-free, Pb-based perovskite films. In our initial demonstration of Ge-Pb perovskite LEDs, we achieve external quantum efficiencies (EQEs) of up to ~13.1% at high brightness (~1900 cd m-2), a step forward for reduced-toxicity perovskite LEDs. Our findings offer a new solution for developing eco-friendly light-emitting technologies based on perovskite semiconductors

A systematic review of objective factors influencing behavior in public open spaces

As a significant part of outdoor built-environment, public open spaces are closely associated with people's daily lives. Studies of outdoor behavior in these spaces can shed light on users' environmental perceptions and contribute to the promotion of physiological and psychological health. Many recent studies are case studies focused where observations, surveys and interviews have been conducted to understand the factors influencing people's behavior on one or few sites or city environments. There have been few reviews related to this topic, and none have been based on the systematic understanding of influencing factors. This paper presents a systematic review of interactions between behavior and the built environment in public open spaces, and highlights the impacts of diverse and objective influencing factors. Followed the rules of PRISMA method (Preferred Reporting Items for Systematic Reviews and Meta-Analyses), 109 papers published in 2000–2021 were selected and reviewed. The distribution of the studied interactions is analyzed, and the impacts of four distinct factors: personal background, location and context, environmental component, and climate stimuli, are extracted, categorized, and specified. Moreover, outdoor health benefits are discussed based on which, crucial factors that require emphasis after the outbreak of COVID-19 are identified. Throughout this paper, behavioral influencing processes, including objective influencing factors, subjective feedback, and the relationships involved, are considered to provide a comprehensive picture. With the robust classification of existing factors, architects, urban designers, policy makers and fellow researches could be easier to get a more comprehensive trend from the past. This paper also provides guidance for future research, especially given that COVID-19 has created huge changes to outdoor needs and customary behavior

Behaviour in public open spaces: A systematic review of studies with quantitative research methods

Public open spaces are important assets that play a significant role in city lives, based on which a great number of behaviour-based studies are being conducted. These studies often use one or more case studies to observe people's preferences and usage habits and to investigate their influencing factors such as outdoor thermal comfort, environmental conditions, urban configuration, and local settings. Because the subject is complex and falls within the purview of multiple academic disciplines, it is a challenging task to understand the current status and development trends of existing studies. To fill this gap, this article presents a systematic review of quantitative evidence-based behaviour studies in public open spaces. Following the PRISMA method and searching using eight academic search engines, full texts of 116 research articles have been included for this review. The main contributions of this review are that: (1) it proposed a relatively complete system that categorizes people's behaviour in public open spaces; (2) it introduced outdoor subjective influencing procedure including behaviour, feeling and health impacts; (3) the review illustrated the distribution of existing research as well as research trends; and finally (4) the article also timely discussed the influence of the COVID-19 on people's behaviour in public open spaces. The authors consider this article to be useful as it can facilitate further behaviour-based studies in public open spaces. With a robust classification and future trend discussion of factors associated, fellow researchers, urban designers, city managers, and policymakers are easier to integrate and use the knowledge learned

The KLF4–p62 axis prevents vascular endothelial cell injury via the mTOR/S6K pathway and autophagy in diabetic kidney disease

Introduction: Diabetic kidney disease (DKD) is a complication of systemic diabetic microangiopathy, which has a high risk of developing into end-stage renal disease and death. This study explored the mechanism underlying autophagy in DKD vascular endothelial cell injury. Material and methods: DKD and vascular endothelial cell injury models were established using Sprague Dawley rats and human umbilical vein endothelial cells (HUVECs). HUVECs overexpressing Kruppel-like factor 4 (KLF4) were constructed by transient transfection of plasmids. Biochemical determination of urinary protein and blood urea nitrogen (BUN), superoxide dismutase (SOD), and creatinine (Scr) levels was performed. Renal pathology was observed by periodic acid–Schiff (PAS) staining. Cell Counting Kit-8 (CCK8), terminal deoxynucleotidyl transferase dUTP nick end labelling (TUNEL), and immunocytochemistry (ICC) were used to analyse the growth and apoptosis of HUVECs. Microtubule-associated protein light chain 3 (LC3) expression was observed by immunofluorescence (IF). The reactive oxygen species (ROS) levels were measured using flow cytometry. Monocyte chemoattractant protein-1 (MCP-1), KLF4, and tumour necrosis factor alpha (TNF-α) levels were detected using enzyme-linked immunosorbent assay (ELISA). The expression of KLF4, p62 protein, and LC3 was analysed using reverse transcription quantitative real-time polymerase chain reaction (RT-qPCR). S6 kinase (S6K), p70 ribosomal S6 kinase (p-S6K), Beclin1, ATG5, LC3, p62, Caspase-3, mammalian target of rapamycine (mTOR), and phsophorylated mTOR (p-mTOR) expressions were detected by western blotting. Results: PAS-positive substances (polysaccharide and glycogen) and S6K protein levels increased, and LC3 protein expression decreased in DKD rats. The levels of urinary protein, BUN, and Scr increased, and KLF4 decreased in DKD rats. High glucose (HG) levels decreased the proliferation and increased the apoptosis rate of HUVECs. The expression of ROS, TNF-α, MCP-1, and p62 increased, while the expression of SOD, KLF4, Beclin1, ATG5, and LC3 decreased in HG-induced HUVECs. KLF4 overexpression significantly increased Beclin1, ATG5, and LC3 protein expression and decreased p62 protein expression compared to the oe-NC group in HG-induced HUVECs. KLF4 overexpression inhibits the expression of Caspase-3, p-mTOR, and p-S6K in HG-induced HUVECs. Conclusions: KLF4–p62 axis improved vascular endothelial cell injury by regulating inflammation and the mTOR/S6K pathway in DKD

Differential effects of exogenous and endogenous cueing in multi-stream RSVP: implications for theories of attentional blink

The attentional blink (AB) refers to the finding that performance on the second of two targets (T1 and T2) in a rapid serial visual presentation (RSVP) stream is impaired when the targets are presented within 200–500 ms. To explore the possible interaction between spatial attentional orienting and temporary attentional deficits, this study used central (endogenous) and peripheral (exogenous) cues in a multi-stream RSVP task and compared the endogenous and exogenous cueing effects inside and outside of the AB period. While the endogenous cueing effect was constant in magnitude over time, the exogenous cueing effect was significantly larger inside than outside of the AB period. Theoretical implications of these findings for the interaction between attention mechanisms in spatial and temporal domains are discussed

Taking the pulse of COVID-19: A spatiotemporal perspective

The sudden outbreak of the Coronavirus disease (COVID-19) swept across the world in early 2020, triggering the lockdowns of several billion people across many countries, including China, Spain, India, the U.K., Italy, France, Germany, and most states of the U.S. The transmission of the virus accelerated rapidly with the most confirmed cases in the U.S., and New York City became an epicenter of the pandemic by the end of March. In response to this national and global emergency, the NSF Spatiotemporal Innovation Center brought together a taskforce of international researchers and assembled implemented strategies to rapidly respond to this crisis, for supporting research, saving lives, and protecting the health of global citizens. This perspective paper presents our collective view on the global health emergency and our effort in collecting, analyzing, and sharing relevant data on global policy and government responses, geospatial indicators of the outbreak and evolving forecasts; in developing research capabilities and mitigation measures with global scientists, promoting collaborative research on outbreak dynamics, and reflecting on the dynamic responses from human societies.Comment: 27 pages, 18 figures. International Journal of Digital Earth (2020

Integrated Computational Model of Lung Tissue Bioenergetics

Altered lung tissue bioenergetics plays a key role in the pathogenesis of lung diseases. A wealth of information exists regarding the bioenergetic processes in mitochondria isolated from rat lungs, cultured pulmonary endothelial cells, and intact rat lungs under physiological and pathophysiological conditions. However, the interdependence of those processes makes it difficult to quantify the impact of a change in a single or multiple process(es) on overall lung tissue bioenergetics. Integrated computational modeling provides a mechanistic and quantitative framework for the bioenergetic data at different levels of biological organization. The objective of this study was to develop and validate an integrated computational model of lung bioenergetics using existing experimental data from isolated perfused rat lungs. The model expands our recently developed computational model of the bioenergetics of mitochondria isolated from rat lungs by accounting for glucose uptake and phosphorylation, glycolysis, and the pentose phosphate pathway. For the mitochondrial region of the model, values of kinetic parameters were fixed at those estimated in our recent model of the bioenergetics of mitochondria isolated from rat lungs. For the cytosolic region of the model, intrinsic parameters such as apparent Michaelis constants were determined based on previously published enzyme kinetics data, whereas extrinsic parameters such as maximal reaction and transport velocities were estimated by fitting the model solution to published data from isolated rat lungs. The model was then validated by assessing its ability to predict existing experimental data not used for parameter estimation, including relationships between lung nucleotides content, lung lactate production rate, and lung energy charge under different experimental conditions. In addition, the model was used to gain novel insights on how lung tissue glycolytic rate is regulated by exogenous substrates such as glucose and lactate, and assess differences in the bioenergetics of mitochondria isolated from lung tissue and those of mitochondria in intact lungs. To the best of our knowledge, this is the first model of lung tissue bioenergetics. The model provides a mechanistic and quantitative framework for integrating available lung tissue bioenergetics data, and for testing novel hypotheses regarding the role of different cytosolic and mitochondrial processes in lung tissue bioenergetics